The products from legacy players are inclined towards improving investor workflows at organisational and individual levels
By Srinath Srinivasan
There are nearly a dozen of startups today in India, that are either domestic or international, which are in the business of algorithmic trading (algo trading), as part of the broader fintech ecosystem in India. As is the case today, these startups are at the forefront of technological disruption and aim to scale quickly. On the other end of the spectrum are legacy players such as William O’Neil which are employing their own tech teams to build a suite of products to enable algorithmic trading. As a methodology driven company, William O’Neil incorporates its CANSLIM technique into algorithms. CANSLIM takes into account a number of factors to make the most out of investments, including current quarterly earnings, annual earnings, new products and services that are launched by companies listed in the open markets of the world.
The market research biggie is addressing use cases in B2B channel, which also drives 70% of its revenue. Says Anupam Singhi, CEO, William O’Neil, India: “Using technology allows us to have certain advantages over competitors and improving our services.” With over 100 years of proprietary data used to train algorithms, Singhi believes that the services can be scaled across verticals with high levels of accuracy. “Our quant team has developed an end-to-end framework that starts with our factor research library and ends with paper trading and live operations,” explains Singhi, talking about the development of the algorithms.
With over 130 people working on the tech in Bengaluru, there are also doctorates, mathematicians, researchers and portfolio managers to have multiple levels of verifications and validations. These verifications ensure better risk adjusted returns and help satisfy the mandate for William O’Neil’s clients. Multiple factors associated with the market are taken from the factor research library. Some of the IP built out of Bengaluru are patented and product learnings from the West are also brought to India. “In the US we have been running some of these products for 30 years. What matters to India at the moment is to modify and refine it for the nascent market here,” says Singhi.
Today, for instance, domestic algo-trading startups are gradually diverisfying into mutual fund and portfolio management with their in-house products, at a flat rate and with API enabled integration. While these are more towards driving revenue and customer acquisition, the products from legacy players are inclined towards improving investor workflows at organisational and individual levels. Brokerages like IIFL and 5paisa.com are some of the early adopters of this tech into their workflow. Artificial Intelligence and Machine Learning are at the core of the firm’s tech systems. Leveraging digital has helped William O’Neil grow 3x since 2016. Singhi says that interfacing these algorithms to voice assistants will also be a top priority in the coming years as they chase a market of `500 crore in the next five years.
In 2018, markets regulator Sebi asked stock exchanges to implement shared co-location services to cut costs which would benefit small and medium businesses. This would increase their access to algo trading drastically, given the mobile penetration and data infrastructure in the country today. Riding on this wave allows players such as William O’Neil to tap into SMEs as well as every mobile user who wishes to engage in trading.
“In comparison to the US, India is a tiny market. But that is not how one should approach the market. As a standalone market, India is huge. There are lots of family offices and first-time investors using the mobile phone as a means to trade. It is a gradual process leading towards a boom,” says Singhi.
In order to stay relevant in the long term, companies such as William O’Neil are expected to diversify into advisory roles which are omni-channel in nature. Next to retail, stock trading could see more of omni-channel offerings where brokers and institutional managers can be found using more digital tools as businesses evolve their investment behaviours. While there aren’t many challenges in terms of technology and handling macro economic factors like market slowdowns, the real challenge lies in scaling up and being bullish in acquiring customers.